COVID-19 classification from ground glass opacities of radiologic images via pytorch convolutional neural network

• Main Authors: Que, Carlos Joshua V., Vjuan, Macario S., Apostol, Alyanna Teresa Q.
• Format: text
• Language: English
• Published: Animo Repository 2022
• Subjects: Image processing; Programming languages (Electronic computers); COVID-19 (Disease); Physics
• Online Access: https://animorepository.dlsu.edu.ph/etdb_physics/16; https://animorepository.dlsu.edu.ph/context/etdb_physics/article/1018/viewcontent/2022_Apostol_Que_Vjuan_COVID_19_Classification_from_Ground_Glass_Opacities_of_Radiologic_Full_text.pdf
• Institution: De La Salle University

The researchers performed COVID-19 classification from the ground glass opacities (GGOs) of radiologic images of suspected patients by convolutional neural network (CNN) program using Pytorch Tensor, a python script programming language data type. Due to the increasing number of COVID -19 variants,...